cfg = dict(
    gpus = [0, 1, 2,3],
    cuda = True,
    workers = 8,

    output_dir = 'output/mnv24',
    pretrain = '',

    dataset = dict(
        name = 'WiderFace',
        root = '/data0/lfx/widerface',
        anno_root = '/data0/lfx/widerface/anno',
        min_face = 12, 
        image_size =  [800, 800],
    ),

    model = dict(
        name = 'mobilenetv2',
        num_classes = 1,
        pretrain = False,
        fpn_channels = [24, 32, 96, 320],
        return_layers = ['layer1', 'layer2', 'layer3', 'layer4'],
    ),

    train = dict(
        batch_size_per_gpu = 10,
        max_epoch = 120,
        optimizer = 'adam',
        lr = 5e-4,
        lr_factor = 0.1,
        lr_step = [70, 100],
        wd = 1e-4,
        moentum = 0.9,
        heatmap_weight = 1.0,
        ltrb_weight = 3.0,
        landmark_weight = 0.1,
    ),

    test = dict(
        batch_size_per_gpu = 10,
    ),
)